MongoDB Reviews

Snowflake and Redshift are much more mature and have been around longer. MongoDB is definitely much less expensive and if you are in a startup, this is an almost for-sure option. Redshift can be slow and Mongo is much faster. However, losing the relational database aspect could be unappealing to the more senior SQL developers on your team.

I just felt MongoDB was easier to use and more cost-effective. Aggregation pipelines are great.

Also, using DocumentDB, and both are good, each was chosen based on the developer's expertise. So take advantage of in-house skills.

It's very fast and easiest to use. Many companies are using this nowadays. It's helped to complete many software products very quickly so the year income has increased compared with last years. Many programmers are now leaning this tool as back end developers so that we changed to this tool for future works.

Your default choice should not be MongoDB in my opinion. Most user-facing systems are relational by nature so a well known and reliable SQL database would be easier to maintain and simpler to develop long term. If you highly value speed of development go with Firebase. If you have a big data type of scenario, Casandra or Elastic-search are probably a better suite. You should not use MongoDB if you don't have someone proficient at it, as you are far more likely to shoot yourself in the foot compared to other solutions.

MongoDB and Cassandra are both database system from the NoSQL family. MongoDB can be used in lots of use cases while Cassandra has a specific usage. There are some features that MongoDB provides efficiently while Cassandra doesn't and vice-versa. Like, you can update the data in Cassandra at a very high rate with good performance, but performance will have a dip if you do the same on MongoDB.

We selected MongoDB because of the following

• Ease of deployment
• Use and provisioning on their cloud
• Simple learning path for creating and building an app without much fuss about syntaxes
• Beautiful graphical interface for quick setup
• Cost to use and implement is very beneficial for small and midsize projects
• On-demand scalability and performance improvement
• Good support model and functionalities

MongoDB is our go-to database solution for any project, and the more we work with it the more we love it. Some say that NoSQL is pointless... Our developers wholeheartedly disagree, because they love working with it. Though both NoSQL and SQL have their purposes, in most projects the choice comes down to what the developers prefer, and in our case that's NoSQL. Just be aware of when SQL is the right choice for your use case.

It does not belong to certain cloud platforms. MongoDB is an independent program that works with any cloud platform including Amazon Web Services and the Google Cloud Platform. For companies who want to maintain a cloud agnostic structure, MongoDB is a great choice for NoSQL databases. You can simply combine MongoDB with either of the cloud platforms to make your own clusters.

We wanted to use free ware relational database for our need. MongoDB was perfect fit.

MongoDB is probably the most famous NoSQL database of the moment. it has become one of the most promising startups. Some companies that currently use MongoDB are Foursquare or eBay. This type of database is designed to perform queries and aggregations on large amounts of data. They work in a similar way to relational databases, but storing columns of data instead of records.

MongoDB is the best NoSQL database out there. There are others, but Mongo has the largest community, is very easy to set up, and is extremely performant. Compared to a relational DB (like MySQL or Postgres) is like comparing apples and oranges. One isn't better or worse than the other. It more depends on the particular data you are working with and what you need to do with that data. That will determine which option to go with.

MongoDB seemed to be a bit more robust in schema models at the time of choosing it over Firebase. Firebase was also still in beta at the time. Since then I have used both MongoDB and Firebase Real-time Database, and feel that firebase is easier to get running and started, but I still prefer some of the data structures and querying of MongoDB.

Mongo is very easy to use and have a low learning path

Looking into PostgreSQL happened post move to Mongo. Had we considered both options at the time we likely would have went with PostgreSQL. We may migrate at some point in the future but currently it doesn't make sense.

We tend to choose MongoDB when we're faced with a particular situation: we know that we need a NoSQL database in general, and want an open-source implementation that allows us to prevent against platform lock-in. Amazon's new DocumentDB product even allows us to choose to use MongoDB's tooling and community, even in cases where we are not explicitly implementing MongoDB!

In the beginning, we considered several products in the market. Since our project was a science and research project, our budget wasn't as big as a commercial project, but still, we wanted the product to be scalable so that we could deal with "smooth transition" from research to commercialization. At the end of the discussion, we choose MongoDB rather than other products like Cassandra, simply because we could hire good developers who had expertise in MongoDB. Our management left that decision to developers and let them choose since they knew what's good for them.

I love MySQL, but again, it's a totally different use-case. For something with so much varied data in no particular form or structure that needs to be pooled together in a "data lake," a NoSQL solution like MongoDB is an easy choice. It makes it so much easier not having to deal with constraints you would be responsible for defining otherwise.

MongoDB is very easy to use and the best advantage is the NoSQL database. No concept of the relational database.

I recently tried out Firestore from the Google firebase family of development products. While it allows structuring of data similar to MongoDB, it handles things a little differently. MongoDB documents are incredibly flexible and can be structured really any way you can structure a JSON object with a few additions. I felt like Firestore's query syntax was super easy to grasp, although it wasn't as powerful or flexible straight away as a MongoDB query. For example, you can combine a lot more logical operators easily in a Mongo query while I couldn't figure out how to do so on a Firestore query. And there's no regex search for text-based/full-text searching in Firestore like there is in MongoDB. I ended up ditching Firebase after a while because it had other limitations that weren't right for our project. However, I would still choose it for certain projects if I found it to be a good fit for the project and benefited from having an integrated data layer. It made a lot of other app development hurdles like authentication painless and easy.

I only briefly looked at CouchDB after I already began using MongoDB. Naturally, I have used many relational SQL databases.

Since MongoDB did everything I needed, I saw no need to look around for alternatives.

(Okay, full disclosure. I am an "association" vs "inheritance" object-oriented snob. In Rails, ActiveRecord implements persistence via inheritance for SQL databases. The MongoDB gems like mongoid and mongomapper add persistance via association. Boom!)

MongoDB is the most complete database of NoSQL type. In my opinion, it has all the tools for a good development of a database. I have not had problems when using the application.

optimize web application.

SQL server is ancient, and Couchbase doesn't let you accomplish anything special--it's too basic, especially from a security standpoint.